Recent advances in wireless network packet transmission speed and range have enabled many new exciting wide-area audio and or video applications. For example, it is now practical to install wireless mobile surveillance networks to improve safety and emergency response times in office and residential campus settings, for surveillance in city streets, oil and mine fields, warehouses, and factory floors. Wireless IPTV has emerged to reach mass mobile handheld devices on the street in real time and Web 2.0 based, multimedia-rich computing and communications are flourishing on intelligent wireless devices for instant information sharing and retrieval. In order to maintain a high level of performance, the typical goal of such wireless, multimedia applications is to maximize throughput in terms of the product of the transmission rate and the frame receipt success ratio (frames received/time period).
One of the problems associated with using wireless, mobile devices to receive multimedia signals is that the condition of the radio link between a transmitting device and a receiving device can change depending upon whether either or both of the devices are in motion, depending upon environmental conditions and the proximity to other devices broadcasting in the same frequency band. The varying condition of the signal is due in large part to interference from other wireless devices, to obstructions to the radio signal that exist in the environment and is due to the distance between the transmitting and receiving devices. Wireless transmission technologies that are implemented on wireless, mobile devices which run multi-media applications have been developed to operate at multiple different transmission rates in order to accommodate the changing signal conditions, and some of these different transmission rates can employ different modulation schemes depending upon the rates susceptibility to interference. So, for instance, a BPSK modulation scheme, which is robust in the presence of interference, can be employed for relatively lower link rates and OFDM, which is robust in the presence of multipath distortion can be employed as a modulation scheme for high link rates. Also, the QPSK module scheme is suitable for higher link rates and operates with higher power and so the signals can be transmitted over greater distances.
A number of wireless audio/video applications are available that are based on wireless technology such as the IEEE 802.11 standards. The 802.11 standards have been extended to provide a number of different link rates at which signals can be transmitted. So, for instance, 802.11b signals can be transmitted at 1 Mbps, 2 Mbps, 5.5 Mbps or 11 MBps with the transmission rate largely dependent upon the signal to noise/interference ratio (SINR) measured at a receiver. Dynamic rate control methods are used to make the SINR measurements and to automatically change the transmission rate so as to maximize throughput. Such dynamic rate control methods are typically referred to as automatic transmission rate adaptation or simply rate adaptation. As the SINR increases, a rate adaptation method can operate to automatically increase the packet transmission rate.
Rate adaptation methods usually achieve their design goal fairly well, and differ only in the details with respect to how the channel quality is evaluated and predicted, with respect to how to measure the frame loss ratios, and how to increase or decrease the channel rate. Popular throughput evaluation tools, e.g., iperf that derives throughput by blasting UDP or TCP traffic, do report good throughput results. While such rate adaptation methods work well for non-real-time traffic, this is not the case with real-time traffic. For real-time traffic transport, the optimal throughput or the channel-rate frame-success-ratio product does not necessarily translate to the best video playback quality. In fact, all existing rate adaptation methods perform poorly for video streaming, for instance. Video mosaic is often observed in the playback due to excessive random frame losses. Chunky and shaking images are frequent due to the losses of synchronization followed by lengthy re-synchronizations to the video source. The fundamental problem is that when the gap between two neighboring rates is large, rate adaptation methods favor the higher rate even though the packet loss ratio is relatively high. In the IEEE 802.11 standard, for example, the overall throughput (or channel-rate-frame-success-ratio product) at the 9 Mbps packet transmission rate is higher, with packet loss ratio up to 38%, compared with the maximum throughput possible at the 6 Mbps packet transmission rate with a packet loss ratio of zero. As a result, all existing throughput-optimizing rate adaptation methods select a higher packet transmission rate, even when the packet loss ratio is as high as 23% to 38%, before the next lower rate is considered. Consequently, the wireless networks tend to stabilize in a state where the packet loss ratios, perceived by the end-to-end real-time transport, are orders of magnitudes higher than those in wired networks. Designed to optimize throughput in wired networks where the incidence of packet loss is usually much lower, existing video decoders are not able to operate in a wireless environment to process real-time streams of video information, where the incidence of packet loss is high, such that the video is high and is played without artifacts.
As opposed to overall packet throughput, packet delay and packet loss are more important parameters to manage for the optimum operation of a wireless, real-time multimedia application. So, in lieu of the limitations to existing throughput based rate adaptation methods, it would be advantageous if the model according to which a rate adaptation method is designed is based upon parameters most critical to the optimum operation of a wireless, real-time multimedia application; namely, the packet delay and packet loss parameters.